Napa is the happiest U.S. city, according to a new analysis of tweets. / Eric Risberg, AP

by Kim Painter, Special for USA TODAY

by Kim Painter, Special for USA TODAY

It's not just the wine. But the word "wine," along with "beauty," "hope," "food," and other words with happy vibes, help make Napa, Calif., the happiest city in the USA, at least according to a new analysis of 10 million tweets. Beaumont, Texas, comes in last among 373 cities, thanks to lots of swearing and a shortage of "awesome" and "amazing."

Among states, Hawaii is first (think "beach") and Louisiana is last (thanks, again, to "an abundance of profanity").

The study, from mathematicians at the University of Vermont, is the latest to tap Twitter's 140-character, real-time posts to see how we're feeling. Previous studies found that Twitter users are happiest on Sunday mornings, saddest on Thursday evenings and prone to perk up on Christmas and other holidays.

The new study used a list of 10,000 words rated on a 10-point scale as happy, sad or neutral to score tweets from 2011 that carried geographic tags. The researchers threw out neutral words (such as "the," "of" and "and") and looked at how often the happy and sad words showed up in different cities and states, lead researcher Lewis Mitchell says.

Words such as "hate," "terrorist," "earthquake" and "greed" were high on the sad list, he says. Happy words included "happy," "reunion," "lol" (laughing out loud) and nature terms, which helps explain how tweets from Maine, which mentioned lots of "forests" and "rivers," came in only second to those from Hawaii on the happy list.

Other relatively happy states included Nevada, Utah and Vermont. After Louisiana, the least happy states were Mississippi, Maryland, Delaware and Georgia.

Researchers did not read the tweets for context or try to sort out travelers from residents, Mitchell says. The biggest potential weakness of the study is that it only includes Twitter users, who make up just 15% of adults and tend to be young. But many of the findings track those from surveys, including the ongoing Gallup-Healthways Well-Being Index, Mitchell says. They also track with research showing happiness is partly linked to income.

Napa Mayor Jill Techel, not too surprisingly, finds the study convincing: "We've got the wonderful weather, the fabulous food and wine and the views," she says. "It's a great place."

A Beaumont official, also unsurprisingly, disagreed with his city's ranking: "Overall, only a small share of society is tweeting, therefore we disagree with the findings of this study, as it is not a true representation of Beaumont," said Dean Conwell, executive director of the Beaumont Convention and Visitors Bureau, in an e-mail. "We invite everyone to visit Beaumont and experience all the happiness we have to share, including our #unicorns, #kittens, and #rainbows."

Defenders of the city also showed up in the comment section of a blog post Mitchell wrote. "I have noticed that people in Texas tend to be happier than average folks from the (north)," a commenter identified as Luis wrote. "The fact (that) there is a lot of profanity in the tweets (is) not really an indication of sadnessâ?¦Texans just like to talk profanity, and sometimes in a very happy context."

Mitchell said it's true that swear words aren't always a sign of sadness. In fact, the study threw out one profanity, commonly known as the f-word, because people use it in so many ways. But, he says, the research shows when people use swear words, they also tend to use other negative words like "hate" or "sick" or "war," making them generally reliable predictors of negativity.

In the future, the Vermont team and others hope to use these methods to track changes in happiness and health, not only for states and cities, but even in neighborhoods, Mitchell says.

The study has not yet been published in a scholarly journal or reviewed by other researchers in the field. Instead, it is posted at a public research site called arxiv.org.

Top spots:

The happiest states, based on a University of Vermont analysis of 10 million tweets from 50 states and the District of Columbia:

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